If you are new to the site you may be wondering what kinds of interesting facts you can discover from searching our database. Currently, there are two types of correlations: Political Correlations and Cross Correlations.
Political correlations can be fun. They allow you to map the political allegiance of a state to a statistic gathered for non-political purposes. Do stated party platforms hold up against how the individuals in states supporting those platforms live their daily lives? Using our Political Correlation tool you can select exactly what states are red (Conservative/Republican), blue (Liberal/Democratic), or purple (inconsistent in their voting patterns). For the correlations shown we used a default value of the state's electoral college going to a Republican candidate at least 60% of the time since 1990 as a red state. Similarly, if their electoral college went democratic 60% of the time since 1990 the state was colored blue. Any states left were colored purple. Using our default definition of red states and blue states we discovered interesting correlations between a few facts. We hope you find them interesting as well.
Cross correlations, while not carrying political pizazz, can be even more interesting. Often they support connections we anecdotally believe to be true with concrete statistics that shouldn't be ignored. While the numbers are compelling, often it's the colorization of the map that tells the strongest story. How different are our states when it comes to various issues? If for example we correlate the use of heating oil to each state we would expect that the northern states have a higher value and the southern states. Do all statistics have a natural distribution related to state location or culture? In general is there no meaningful correlation between measured statistics any geographic grouping of states? What aspects of a statistic make it sensitive to a state’s boundaries? While it is obvious there is a causation related to heating oil usage and the geographic location of a state, the same relationship is not as oblivious with other statistics.
A perfect example of a correlation that does not have an obvious geographical connection is the obesity rate statistic. As it turns out a geographic area of the county, one that we call the bacon belt, has the preponderance of the county’s most obese people. Why one area of the country would rate so highly in the frequency of obesity is not superficially clear. However, when we look at a state's ranking by Freedom rating no prejudice to any particular region exists.
The power comes from when we correlate one statistic with another. What happens if you correlate a state's rate of obesity with its longevity? Are all those medical pundits telling you to lose weight onto something? Explore further and you will find your answers.
States Colorized by Freedom Ranking
States Colorized by Rate of Obesity
Here are some quick political correlations that we found interesting. Please stay tuned, we will update our exploration in greater detail shortly.
Without making too much of a generalization we were surprised to find that although red states preach family values and criticize the idea of gay marriage as one that would destroy the sanctity of the institution of marriage that they have a higher divorce rate than blue states.
However, when we look at military recruitment rates we see that the vocalized patriotism of red states is backed up with a significantly higher percentage of recruits than blue states.
When we shift gears to economics, a prevailing theme that conservatives tout is that the ultra rich shouldn't pay a higher percentage rate in taxes than the less fortunate.
What is surprising is that although the red states have this view, they actually have a significantly lower number of ultra rich individuals and and overall lower median household income. Therefore, they are not looking after their interests, rather those in the other states.